Podcast Summary: The Disruption in the AI Market
Podcast Title: Thoughts on the Market
Host/Author: Morgan Stanley
Episode Title: The Disruption in the AI Market
Release Date: February 7, 2025
Introduction to DeepSeq’s Breakthrough
In the February 7th episode of Thoughts on the Market, Vishi Tirupator, Morgan Stanley's Chief Fixed Income Strategist, delves into the recent seismic shift in the AI landscape triggered by DeepSeq, a Chinese AI startup. Tirupator highlights that DeepSeq has unveiled two open-source large language models (LLMs) that rival their American counterparts in performance but at a significantly reduced cost. This development isn’t just a technological milestone but a catalyst for broader economic and market implications.
“Deepseek, a Chinese AI startup, has developed two open source large language models, LLMs, that can perform at levels comparable to models from American counterparts at a substantially lower cost.” [00:32]
Market Reaction and Immediate Impact
The announcement of DeepSeq’s innovations sent shockwaves through the equity markets. On January 27th, the revelation led to a drastic drop, wiping out nearly a trillion dollars in the market capitalization of listed U.S. technology companies. Although the market has since recovered a portion of these losses, the initial impact underscores significant investor anxiety regarding the competitive dynamics of the AI sector.
“This news set off shockwaves in the equity markets that wiped out nearly a trillion dollars in the market cap of listed US technology companies on January 27.” [00:32]
Historical Context: Efficiency Gains in Computing
Tirupator draws a parallel between DeepSeq’s advancements and historical efficiency gains in computing. He references the 1990s investment boom, which was driven by firms replacing depreciated capital and the sharp decline in computing costs relative to output.
“The history of computing is replete with examples of dramatic efficiency gains. The Deep SEQ development is precisely that, a dramatic efficiency improvement which in our view drives incremental demand for AI.” [00:32]
Michael Gapin, Morgan Stanley’s US chief economist, is cited to emphasize that similar efficiency gains can spur investment.
“If efficiency gains from Deepseek reflect a similar phenomenon, we may be seeing early signs the cost of AI capital is coming down and coming down rapidly in turn. That should support the outlook for business spending pertaining to AI.” [00:32]
Investment Implications: AI Capital and Business Spending
The reduction in AI capital costs is expected to bolster business investment in AI infrastructure. Tirupator posits that as the cost diminishes, businesses are likely to increase their spending on AI technologies, fostering an environment ripe for innovation and productivity enhancements.
“That should support the outlook for business spending pertaining to AI.” [00:32]
Jevons Paradox and Increased AI Consumption
Tirupator introduces the concept of the Jevons Paradox, which suggests that as technological advancements make resources cheaper to use, the overall demand for those resources increases. Applied to AI, the decreasing cost of AI technologies like LLMs is anticipated to lead to their more widespread adoption, both in consumer and enterprise contexts.
“As technological advancements reduce the cost of using a resource, the overall demand for the resource increases, causing the total resource consumption to rise.” [00:32]
This phenomenon is expected to drive a transition of AI from being a niche innovation to a more generalized tool, accelerating the pace of AI-enabled product innovations and broader market adoption.
“Cheaper and more ubiquitous technology will increase its consumption. This enables AI to transition from innovators to more generalized adoption and opens the door for faster LLM enabled product innovation.” [00:32]
Macro versus Micro Perspectives
From a microeconomic standpoint, Morgan Stanley’s equity research experts believe that the DeepSeq development is unlikely to significantly reduce capital expenditures related to AI infrastructure. Instead, it is seen as an enabler for increased investment and productivity growth at the macroeconomic level.
“From a macroeconomic perspective, there's a good case to be made for higher business spending related to AI as well as productivity growth from AI.” [00:32]
Tirupator emphasizes that while individual stocks may exhibit varying performance, the overall economy is poised to benefit from the efficiencies and competitive advantages introduced by such AI advancements.
“We think it's unlikely that the Deep SEQ development will meaningfully reduce capex related to AI infrastructure. From a macroeconomic perspective, there's a good case to be made for higher business spending related to AI as well as productivity growth from AI.” [00:32]
Conclusion: Constructive Outlook on AI’s Transformational Promise
Tirupator concludes with an optimistic view of AI’s future, asserting that DeepSeq’s breakthrough exemplifies the potential for significant efficiency gains in AI technologies. These advancements are expected to foster competition, drive wider adoption, and ultimately lead to substantial productivity improvements across the economy.
“Deep SEQ illustrates the potential for efficiency gains, which in turn foster greater competition and drive wider adoption of AI. With that premise, we remain constructive on AI's transformational promise.” [00:32]
Key Takeaways
- DeepSeq’s Innovation: Development of cost-effective, high-performance LLMs by a Chinese startup has significant market implications.
- Market Impact: The announcement led to a temporary but substantial decline in U.S. technology market capitalization.
- Historical Parallel: Similar to the 1990s computing advancements, DeepSeq’s efficiency gains are expected to boost AI demand.
- Investment Outlook: Reduced AI costs likely to increase business investment in AI infrastructure, driving economic growth.
- Jevons Paradox: Cheaper AI technologies will enhance their adoption and consumption, accelerating innovation.
- Economic Perspective: While individual stocks may vary, the broader economy stands to gain from increased AI investment and productivity.
- Optimistic Future: Morgan Stanley maintains a positive outlook on AI’s role in transforming business and economic landscapes.
Notable Quotes:
- “Deepseek... can perform at levels comparable to models from American counterparts at a substantially lower cost.” — Vishi Tirupator [00:32]
- “The Deep SEQ development is precisely that, a dramatic efficiency improvement which in our view drives incremental demand for AI.” — Vishi Tirupator [00:32]
- “Cheaper and more ubiquitous technology will increase its consumption...” — Vishi Tirupator [00:32]
- “We think it's unlikely that the Deep SEQ development will meaningfully reduce capex related to AI infrastructure.” — Vishi Tirupator [00:32]
This episode of Thoughts on the Market provides a comprehensive analysis of how DeepSeq’s advancements in AI technology are poised to reshape the market dynamics, influence investment strategies, and contribute to broader economic growth through enhanced productivity and widespread AI adoption.